Featured Product

    Risk Data Management by the Numbers

    Of all data integration projects either fail completely or significantly overrun their budgets.
    42% of respondents have allocated this budget or higher for IFRS 9 compliance.
    Knowledge and skills age so rapidly that the likelihood of employee error approaches 100% by the end of the five-year period.
    We know of one leading commercial bank that employs 20 full time workers to aggregate and clean data in preparation for the FR Y-14Q quarterly commercial data submission.
    The correct full model is chosen 59% of the time. Overall, the inflation coefficient is statistically significant in around 67% of cases, whereas the unemployment rate coefficient is significant 91% of the time.
    Main components of an Insurance Analytics Platform (IAP) architecture.
    From our analysis of similar initiatives and the preparatory work involved, we expect that the ECB will consider between 24 and 150 – or more – attributes per loan for inclusion in AnaCredit.
    The final portfolio for analysis comprised approximately 43,700 securities, which effectively represent the structured finance universe of non-agency transactions.
    As a result, the accuracy of liquidity-monitoring models depends on the ability to evaluate realistic credit transitions over a time horizon as short as 30 days.
    Surprisingly, 14 out of 30 G-SIBs revealed that they will not be fully compliant with at least one of the Basel Committee’s regulatory principles by the deadline in 2016.
    Between June 1997 and March 1998, GDP contracted by nearly 6% in Korea, 9% in Thailand, and 14% in Indonesia. Equity valuations plummeted by 50% or more in the affected countries.
    In the case of commercial loan volume, for instance, the Federal Reserve Board has quarterly data stretching back to the late 1940s.
    As Published In: